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This book presents a comprehensive overview of the basics of
Hindustani music and the associated signal analysis and
technological developments. It begins with an in-depth introduction
to musical signal analysis and its current applications, and then
moves on to a detailed discussion of the features involved in
understanding the musical meaning of the signal in the context of
Hindustani music. The components consist of tones, shruti, scales,
pitch duration and stability, raga, gharana and musical
instruments. The book covers the various technological developments
in this field, supplemented with a number of case studies and their
analysis. The book offers new music researchers essential insights
into the use the automatic concept for finding and testing the
musical features for their applications. Intended primarily for
postgraduate and PhD students working in the area of scientific
research on Hindustani music, as well as other genres where the
concepts are applicable, it is also a valuable resource for
professionals and researchers in musical signal processing.
This book presents a comprehensive overview of the basics of
Hindustani music and the associated signal analysis and
technological developments. It begins with an in-depth introduction
to musical signal analysis and its current applications, and then
moves on to a detailed discussion of the features involved in
understanding the musical meaning of the signal in the context of
Hindustani music. The components consist of tones, shruti, scales,
pitch duration and stability, raga, gharana and musical
instruments. The book covers the various technological developments
in this field, supplemented with a number of case studies and their
analysis. The book offers new music researchers essential insights
into the use the automatic concept for finding and testing the
musical features for their applications. Intended primarily for
postgraduate and PhD students working in the area of scientific
research on Hindustani music, as well as other genres where the
concepts are applicable, it is also a valuable resource for
professionals and researchers in musical signal processing.
The book opens with a short introduction to Indian music, in
particular classical Hindustani music, followed by a chapter on the
role of statistics in computational musicology. The authors then
show how to analyze musical structure using Rubato, the music
software package for statistical analysis, in particular addressing
modeling, melodic similarity and lengths, and entropy analysis;
they then show how to analyze musical performance. Finally, they
explain how the concept of seminatural composition can help a music
composer to obtain the opening line of a raga-based song using
Monte Carlo simulation. The book will be of interest to musicians
and musicologists, particularly those engaged with Indian music.
This book forms the much needed strong interface between
algorithmic complexity and computer experiments using a careful
blending of traditional ideas in algorithms with untraditional
research in computer experiments (esp. fitting stochastic models to
non-random data). While establishing the aforesaid interface, the
important role of statistical bounds and their empirical estimates
obtained over a finite range (called empirical O) is discovered as
a bonus. While these bounds are very valuable for the average case,
our research suggests in addition that there is no need to be
over-conservative in the worst case just as the statistical bounds
safeguard against making tall optimistic claims for the best cases.
In short the statistical bounds have a sense of "calculated
guarantee" that is neither too risky nor too conservative. In
parallel computing, with every change of the processor, it can be
argued that it is the weight of the operation that changes. Hence,
if the bound is itself based on weights, it should be deemed as the
ideal one.
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